Internship | Instruction-tuning for physical properties of objects | The Hague
1 maand geleden
About this position
For robots, it’s essential to understand physical properties of objects, such as size, weight and material. Current models are not good at this. Recent developments show improvements via instructing-tuning of vision-language models, e.g. “Physically Grounded Vision-Language Models for Robotic Manipulation” ( Essentially, this approach involves learning preferences that are acquired from human feedback (e.g. object 1 is heavier than object 2). Can we further tailor this to the properties that are relevant for the robot and task at hand? In other words, can we specialize it towards affordances for the current robot? E.g. objects 1 and 2 both have a mass that can be pulled by the SPOT robot, whereas object 3 cannot be pulled by SPOT. If this can be combined with the actual affordance of the object, it can be inferred which object can actually solve the task at hand. In “One-Shot Open Affordance Learning with Foundation Models” ( a model learned fixed relations about object-affordance, e.g. a stone can hold a blanket in the wind. But one stone may be too light, whereas the other is heavy enough. Our goal is an object-property-affordance relation. E.g., the robot should choose the heaviest stone it can pull, because that is the one most likely to achieve the goal (i.e. hold a blanket).
What will be your role?
In this project, you will:
Explore the opportunities of instruction-tuning for vision-language models. Research how such models can learn about affordances and physical properties of objects. Investigate how instruction-tuning can be leveraged to learn such affordances for the specific robot with its given, limited capabilities. Search for possibilities to combine affordance recognition with the physical properties.You will perform this assignment within TNO’s Intelligent Imaging department. The Intelligent Imaging department is a passionate, creative, and dedicated team of professionals (50 people) specialized in developing groundbreaking applications in the field of computer vision. Our team members have diverse backgrounds, ranging from physics to artificial intelligence. Intelligent Imaging is a young and growing department which has built up a lot of expertise over the past years in AI and deep learning.
What we expect from you
You are in the final stages of your master’s in artificial intelligence, computer science, physics, mathematics, electrical engineering, or a similar field, you have experience in programming (e.g. Python) and prior experience with computer vision and deep learning.
The project duration is flexible within the range of 6 to 12 months. Please mention in your application whether you are looking for an internship or a graduation project, the preferred duration of your project and your desired starting date.
What you'll get in return
You want to work on the precursor of your career; a work placement gives you an opportunity to take a good look at your prospective future employer. TNO goes a step further. It’s not just looking that interests us; you and your knowledge are essential to our innovation. That’s why we attach a great deal of value to your personal and professional development. You will, of course, be properly supervised during your work placement and be given the scope for you to get the best out of yourself. Furthermore, we provide:
A highly professional, innovative working environment, with top experts as colleagues. A suitable internship allowance ( euro for wo- and hbo-students, euro for mbo-students, for a full-time internship). Eight hours of leave per internship month (for a full-time internship). A free membership of , where you can meet TNO-colleagues and join , such as sports activities, (work-related) courses or the yearly ski-trip. Use of a laptop. An allowance for travel expenses in case you don’t receive an OV-card.-
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